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Record W3035284715 · doi:10.1111/add.15142

Bidirectional effects between loneliness, smoking and alcohol use: evidence from a Mendelian randomization study

2020· article· en· W3035284715 on OpenAlexfundno aff
Robyn E. Wootton, Harriet Greenstone, Abdel Abdellaoui, Damiaan Denys, Karin J. H. Verweij, Marcus R. Munafò, Jorien L. Treur

Bibliographic record

VenueAddiction · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsnot available
FundersEconomic and Social Research CouncilMedical Research CouncilUniversity of BristolDepartment of Health and Social CareNederlandse Organisatie voor Wetenschappelijk OnderzoekBritish Heart FoundationUniversity Hospitals Bristol NHS Foundation TrustCancer Research UKStichting Volksbond RotterdamNational Institute for Health and Care ResearchMedical Research Council CanadaZonMwNIHR Newcastle Biomedical Research CentreUnited Kingdom Clinical Research Collaboration
KeywordsMendelian randomizationLonelinessMedicineObservational studyConfoundingConcordanceGenome-wide association studyPsychologyClinical psychologyPsychiatryDemographyInternal medicineGeneticsSingle-nucleotide polymorphismBiologyGenetic variants

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: Loneliness is associated with cigarette smoking and problematic alcohol use. Observational evidence suggests these associations arise because loneliness increases substance use; however, there is potential for reverse causation (problematic drinking damages social networks, leading to loneliness). With conventional epidemiological methods, controlling for (residual) confounding and reverse causality is difficult. This study applied Mendelian randomization (MR) to assess bidirectional causal effects among loneliness, smoking behaviour and alcohol (mis)use. MR uses genetic variants as instrumental variables to estimate the causal effect of an exposure on an outcome, if the assumptions are satisfied. DESIGN: Our primary method was inverse-variance weighted (IVW) regression and the robustness of these findings was assessed with five different sensitivity methods. SETTING: European ancestry. PARTICIPANTS: Summary-level data were drawn from the largest available independent genome-wide association studies (GWAS) of loneliness (n = 511 280), smoking (initiation (n = 249 171), cigarettes per day (n = 249 171) and cessation (n = 143 852), alcoholic drinks per week (n = 226 223) and alcohol dependence (n = 46 568). MEASUREMENTS: Genetic variants predictive of the exposure variable were selected as instruments from the respective GWAS. FINDINGS: ]. We found no clear evidence for a causal effect of loneliness on drinks per week (IVW, β = 0.01, 95% CI = -0.11, 0.13, P = 0.865) or alcohol dependence (IVW, β = 0.09, 95% CI = -0.19, 0.36, P = 0.533) nor of alcohol use on loneliness (drinks per week IVW, β = 0.09, 95% CI = -0.02, 0.22, P = 0.076; alcohol dependence IVW, β = 0.06, 95% CI = -0.02, 0.13, P = 0.162). CONCLUSIONS: There appears to be tentative evidence for causal, bidirectional, increasing effects between loneliness and cigarette smoking, especially for smoking initiation increasing loneliness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.053
metaresearch head score (Gemma)0.164
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.164
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.293
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations91
Published2020
Admission routes1
Has abstractyes

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